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A feature-based cost estimation model
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- Author / Creator
- Sajadfar,Narges
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To address the requirement of dynamic pricing and cost control in high-variation product manufacturing, nowadays many companies face the problem of generating quotes and order prices timely, accurately and consistently. This research reports a preliminary investigation on automatic cost estimation with a feature-based semantic model.
A generic semantic model for the purpose of automatic cost estimation is proposed, in which a new concept named cost feature, is suggested. A cost feature can be identified with data mining methods for different targeted clients or products, and conceptually interfaced with product design and manufacturing features. Feature-based mapping model is used to determine feature scope and cost level defined, including all the dependency relations with other domain features. This model is expected to enable a visual, flexible and semantically consistent scheme to address effective and efficient product cost structures, frequent configuration variations and business changes.
Cost feature has been defined by the authors as a unique class in the unified feature modelling system to address the characteristics of cost engineering entities, constraints and dependency relations. This research describes the relations between a cost feature and three engineering sub-models, i.e. machining model, design model and other auxiliary data model by associating tangible and intangible data. Further, semantic relations are investigated in early product design process for dynamic, accurate and visible product cost estimation. This research also discusses cost engineering related functions, associated data structures, and techniques proposed in details.
In addition, this research presents a Cost Estimation (CE) method that has been tailored to apply feature-based engineering concept with data mining algorithms. The method proposed combines linear regression and data mining approaches, leverages the unique strengths of the both, and creates a mechanism to discover cost features. The final estimation function takes the user’s confidence levels for each of the member approaches into consideration such that the application of the method can be phased in gradually in reality by building up the data mining capability. -
- Subjects / Keywords
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- Graduation date
- Fall 2014
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- Type of Item
- Thesis
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- Degree
- Master of Science
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- License
- This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.